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swiftformer-xs-DMAE

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Files changed (11) hide show
  1. README.md +38 -39
  2. all_results.json +9 -9
  3. eval_results.json +5 -5
  4. model.safetensors +1 -1
  5. runs/Dec02_10-09-39_DESKTOP-SKBE9FB/events.out.tfevents.1733155780.DESKTOP-SKBE9FB.15472.0 +3 -0
  6. runs/Dec02_10-11-14_DESKTOP-SKBE9FB/events.out.tfevents.1733155875.DESKTOP-SKBE9FB.14404.0 +3 -0
  7. runs/Dec02_10-12-43_DESKTOP-SKBE9FB/events.out.tfevents.1733155964.DESKTOP-SKBE9FB.12184.0 +3 -0
  8. runs/Dec02_10-12-43_DESKTOP-SKBE9FB/events.out.tfevents.1733156096.DESKTOP-SKBE9FB.12184.1 +3 -0
  9. train_results.json +4 -4
  10. trainer_state.json +204 -204
  11. training_args.bin +1 -1
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
21
  metrics:
22
  - name: Accuracy
23
  type: accuracy
24
- value: 0.7391304347826086
25
  ---
26
 
27
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
31
 
32
  This model is a fine-tuned version of [MBZUAI/swiftformer-xs](https://huggingface.co/MBZUAI/swiftformer-xs) on the imagefolder dataset.
33
  It achieves the following results on the evaluation set:
34
- - Loss: 0.8766
35
- - Accuracy: 0.7391
36
 
37
  ## Model description
38
 
@@ -59,48 +59,47 @@ The following hyperparameters were used during training:
59
  - total_train_batch_size: 64
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
61
  - lr_scheduler_type: linear
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- - lr_scheduler_warmup_ratio: 0.15
63
  - num_epochs: 40
64
 
65
  ### Training results
66
 
67
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
68
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
69
- | No log | 0.86 | 3 | 1.3860 | 0.3261 |
70
- | No log | 2.0 | 7 | 1.3830 | 0.5 |
71
- | 1.3842 | 2.86 | 10 | 1.3756 | 0.5870 |
72
- | 1.3842 | 4.0 | 14 | 1.3494 | 0.6087 |
73
- | 1.3842 | 4.86 | 17 | 1.3039 | 0.6522 |
74
- | 1.3427 | 6.0 | 21 | 1.1962 | 0.6522 |
75
- | 1.3427 | 6.86 | 24 | 1.1310 | 0.6739 |
76
- | 1.3427 | 8.0 | 28 | 1.0778 | 0.6522 |
77
- | 1.1837 | 8.86 | 31 | 1.0276 | 0.6957 |
78
- | 1.1837 | 10.0 | 35 | 0.9928 | 0.7174 |
79
- | 1.1837 | 10.86 | 38 | 0.9710 | 0.7174 |
80
- | 1.0531 | 12.0 | 42 | 0.9735 | 0.6739 |
81
- | 1.0531 | 12.86 | 45 | 0.9385 | 0.6522 |
82
- | 1.0531 | 14.0 | 49 | 0.9601 | 0.6739 |
83
- | 0.9883 | 14.86 | 52 | 0.9369 | 0.6739 |
84
- | 0.9883 | 16.0 | 56 | 0.8928 | 0.6739 |
85
- | 0.9883 | 16.86 | 59 | 0.8825 | 0.6739 |
86
- | 0.8632 | 18.0 | 63 | 0.8743 | 0.6739 |
87
- | 0.8632 | 18.86 | 66 | 0.8479 | 0.6739 |
88
- | 0.8732 | 20.0 | 70 | 0.8341 | 0.6739 |
89
- | 0.8732 | 20.86 | 73 | 0.8134 | 0.7174 |
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- | 0.8732 | 22.0 | 77 | 0.8845 | 0.6739 |
91
- | 0.7524 | 22.86 | 80 | 0.9037 | 0.6522 |
92
- | 0.7524 | 24.0 | 84 | 0.8921 | 0.6304 |
93
- | 0.7524 | 24.86 | 87 | 0.8766 | 0.7391 |
94
- | 0.6843 | 26.0 | 91 | 0.8707 | 0.7391 |
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- | 0.6843 | 26.86 | 94 | 0.8922 | 0.7391 |
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- | 0.6843 | 28.0 | 98 | 0.8862 | 0.6957 |
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- | 0.7112 | 28.86 | 101 | 0.8954 | 0.7391 |
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- | 0.6734 | 34.29 | 120 | 0.9051 | 0.7391 |
104
 
105
 
106
  ### Framework versions
 
21
  metrics:
22
  - name: Accuracy
23
  type: accuracy
24
+ value: 0.10869565217391304
25
  ---
26
 
27
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
31
 
32
  This model is a fine-tuned version of [MBZUAI/swiftformer-xs](https://huggingface.co/MBZUAI/swiftformer-xs) on the imagefolder dataset.
33
  It achieves the following results on the evaluation set:
34
+ - Loss: 113.9792
35
+ - Accuracy: 0.1087
36
 
37
  ## Model description
38
 
 
59
  - total_train_batch_size: 64
60
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
61
  - lr_scheduler_type: linear
 
62
  - num_epochs: 40
63
 
64
  ### Training results
65
 
66
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
68
+ | No log | 0.86 | 3 | 113.9792 | 0.1087 |
69
+ | No log | 2.0 | 7 | 113.9181 | 0.1087 |
70
+ | 114.2395 | 2.86 | 10 | 113.8813 | 0.1087 |
71
+ | 114.2395 | 4.0 | 14 | 113.8116 | 0.1087 |
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+ | 114.2395 | 4.86 | 17 | 113.6986 | 0.1087 |
73
+ | 113.364 | 6.0 | 21 | 113.4798 | 0.1087 |
74
+ | 113.364 | 6.86 | 24 | 113.2337 | 0.1087 |
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+ | 113.364 | 8.0 | 28 | 112.8223 | 0.1087 |
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+ | 111.1062 | 8.86 | 31 | 112.5788 | 0.1087 |
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+ | 111.1062 | 10.0 | 35 | 112.4157 | 0.1087 |
78
+ | 111.1062 | 10.86 | 38 | 112.5536 | 0.1087 |
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+ | 114.7018 | 12.0 | 42 | 111.7043 | 0.1087 |
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+ | 114.7018 | 12.86 | 45 | 111.6553 | 0.1087 |
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+ | 114.7018 | 14.0 | 49 | 111.6134 | 0.1087 |
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+ | 110.4914 | 14.86 | 52 | 111.5980 | 0.1087 |
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+ | 110.4914 | 16.0 | 56 | 111.7616 | 0.1087 |
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+ | 110.4914 | 16.86 | 59 | 111.1580 | 0.1087 |
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+ | 110.734 | 18.0 | 63 | 111.7108 | 0.1087 |
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+ | 110.734 | 18.86 | 66 | 111.5206 | 0.1087 |
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+ | 111.3772 | 20.0 | 70 | 110.8819 | 0.1087 |
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+ | 111.3772 | 20.86 | 73 | 110.8025 | 0.1087 |
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+ | 111.3772 | 22.0 | 77 | 110.3515 | 0.1087 |
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+ | 111.2973 | 22.86 | 80 | 110.2387 | 0.1087 |
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+ | 111.2973 | 24.0 | 84 | 109.8073 | 0.1087 |
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+ | 111.2973 | 24.86 | 87 | 109.8227 | 0.1087 |
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+ | 110.7135 | 26.0 | 91 | 109.6086 | 0.1087 |
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+ | 110.7135 | 26.86 | 94 | 109.5835 | 0.1087 |
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+ | 110.7135 | 28.0 | 98 | 109.5830 | 0.1087 |
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+ | 109.1264 | 28.86 | 101 | 109.1648 | 0.1087 |
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+ | 109.1264 | 30.0 | 105 | 109.0658 | 0.1087 |
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+ | 109.1264 | 30.86 | 108 | 109.2846 | 0.1087 |
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+ | 110.2885 | 32.0 | 112 | 109.0267 | 0.1087 |
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+ | 110.2885 | 32.86 | 115 | 109.0973 | 0.1087 |
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+ | 110.2885 | 34.0 | 119 | 108.8769 | 0.1087 |
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+ | 110.1122 | 34.29 | 120 | 108.8197 | 0.1087 |
103
 
104
 
105
  ### Framework versions
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